Numerical analysis of solutal Marangoni convections in porous media
Bibliographic record
Abstract
Abstract The possibility of instability initiation in porous media by Marangoni convection is studied numerically with a special focus on its application in petroleum engineering and enhanced oil recovery (EOR). Both types of micro‐ and macro‐convections are considered. The finite element method is employed to solve the models numerically. The appropriate Marangoni numbers are introduced according to the model after making equations and boundary conditions dimensionless. In order to evaluate micro‐convections in porous media, the Molenkamp model is extended and validation is performed by comparing concentration maps in a special case. For macro‐convections, a specific concentration distribution is imposed on the boundary to simulate similar conditions in EOR. Results showed that micro‐convections are not strong enough to alter the fluid flow in porous media in applicable ranges of Marangoni numbers and porous media properties. On the other hand, for macro‐convection results, fourteen test cases, each with three different porosities, are defined. As a result, the margin of stability is found and it is also shown that the damping forces of porous media delays the onset of convection.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".